A Bioinformatics Tool for Efficient Retrieval of High-Confidence Terpene Synthases (TPS) and Application to the Identification of TPS in Coffea and Quillaja.

Terpenoids are a class of compounds that are found in all living organisms. In plants, some terpenoids are part of primary metabolism, but most terpenes found in plants are classified as specialized metabolites, encoded by terpene synthases (TPS). It is not obvious how to assign the putative product of a given TPS using bioinformatics tools. Phylogenetic analyses easily assign TPS into families; however members of the same TPS family can synthetize more than one terpenoid-and, in many biotechnological applications, researchers are more interested in the product of a given TPS rather than its phylogenetic profile. Automated protein annotation can be used to classify TPS based on their products, despite the family they belong to. Here, we implement an automated bioinformatics method, search_TPS, to identify TPS proteins that synthesize mono, sesqui and diterpenes in Angiosperms. We verified the applicability of the method by classifying wet lab validated TPS and applying it to find TPS proteins in Coffea arabica, C. canephora, C. eugenioides, and Quillaja saponaria. Search_TPS is a computational tool based on PERL scripts that carries out a series of HMMER searches against a curated database of TPS profile hidden Markov models. The tool is freely available at https://github.com/liliane-sntn/TPS .

Genome-Wide Screening and Characterization of Non-Coding RNAs in Coffea canephora.

Coffea canephora grains are highly traded commodities worldwide. Non-coding RNAs (ncRNAs) are transcriptional products involved in genome regulation, environmental responses, and plant development. There is not an extensive genome-wide analysis that uncovers the ncRNA portion of the C. canephora genome. This study aimed to provide a curated characterization of six ncRNA classes in the Coffea canephora genome. For this purpose, we employed a combination of similarity-based and structural-based computational approaches with stringent curation. Candidate ncRNA loci had expression evidence analyzed using sRNA-seq libraries. We identified 7455 ncRNA loci (6976 with transcriptional evidence) in the C. canephora genome. This comprised of total 115 snRNAs, 1031 snoRNAs, 92 miRNA precursors, 602 tRNAs, 72 rRNAs, and 5064 lncRNAs. For miRNAs, we identified 159 putative high-confidence targets. This study was the most extensive genomic catalog of curated ncRNAs in the Coffea genus. This data might help elaborating more robust hypotheses in future comparative genomic studies as well as gene regulation and genome dynamics, helping to understand the molecular basis of domestication, environmental adaptation, resistance to pests and diseases, and coffee productivity.